MCP.Market

Hardware Probe MCP server

by yamaru-eu·io.github.yamaru-eu/hardware-probe·v1.1.2·7 stars
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Hardware probe for performance diagnostics, thermal monitoring, and LLM optimization.

A86/100grade A
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Safety scan
A86/100

full report

Adoption
Growing

7 stars47 downloads/wk

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If you have run it, two minutes of your experience saves the next person an afternoon.

Hardware Probe tools (11)

write = sends, deletes, buys or posts

Read from the package source without running it. The installed server may list more.

  • analyze_inference_config

    Performs a deep scan for LLM inference optimization: GPU details, real memory bandwidth benchmark, ML runtimes (Ollama, Docker, WSL), and environment variables.

  • analyze_local_system

    Reads the hardware specifications of the local machine: CPU, RAM, motherboard and OS. Returns a structured JSON object.

  • analyze_performance

    Provides real-time system performance: CPU load, memory usage, and top processes.

  • analyze_ram_pressure

    Reports current memory pressure: total/used/free/available memory, swap usage, and top processes by RSS.

  • check_llm_compatibility

    (BETA) Checks if a specific LLM model can run on this machine. Returns optimal quantization and estimated tokens per second. Requires remote API connection.

  • check_storage_health

    Reports per-disk health: type (NVMe/SSD/HDD), vendor, temperature, SMART status, and firmware.

  • diagnose_antivirus_impact

    Detects running antivirus/EDR products and reads their exclusion rules. Checks dev hot paths coverage.

  • get_inference_expert_knowledge

    Returns the expert instructions and rules for optimizing LLM inference on this specific hardware. Call this to learn HOW to interpret analyze_inference_config results.

  • get_llm_recommendations

    (BETA) Recommends the best LLM models that can run locally on this machine. Requires remote API connection.

  • monitor_system_health

    Monitors system metrics (CPU, RAM, Thermal) over a specified duration and returns statistical summary. Useful for diagnosing transient issues during high-load tasks.

  • thermal_profile

    Reports current CPU and GPU thermal and frequency state: temperature, utilization, and fan speed.

Public scan report

scanner v0.1.9 · 2026-09-27 · same rubric, same numbers if you re-run it

no findings
  • Code scan13 source files scanned25/25
  • –Live reliabilityno gateway calls yet and no remote to proben/a
  • –Tool poisoningtools not inspected (local package is not executed); not countedn/a
  • Auth qualitylocal package, no credentials required12/15
  • Maintenancelast push 74 days ago12/15
  • Maintainer identityregistry namespace matches repository owner7/10
Overall 86/100. Components that don't apply are left out of the denominator. Any critical finding is an F.RubricAppeal a findingJSON

How Hardware Probe compares

Against every graded AI and agents MCP server, from our own scans and uptime checks. Updated after each scan run.

Safety score
86/100
higher than 75% of 4,460 AI and agents servers
Tools
11
the typical AI and agents server has 6
Tools that change things
0%
typical: 0%. Fewer write tools means less an agent can break
GitHub stars
7
more than 81% of 2,711 AI and agents servers
Downloads a week
47
more than 39% of 1,538 AI and agents servers with a package

What its tools let an agent do: 11 read

Install Hardware Probe in Claude Code, Cursor or VS Code

Runs npx -y @yamaru-eu/hardware-probe on your machine. Read the scan report first; the gateway never runs local packages.

claude mcp add hardware-probe -- npx -y @yamaru-eu/hardware-probe
Add to Cursor

What the publisher says

From the Hardware Probe repository's README, as published. We do not edit it. Read it on GitHub

Yamaru Hardware Probe (MCP)

Expert system hardware probe and performance diagnostic engine for AI, Gaming, and High-Performance workflows. This is a Model Context Protocol (MCP) server that provides deep system insights beyond simple specifications.

Key Features

  • 🔍 Deep Hardware Inventory: Comprehensive analysis of CPU, RAM, GPU (VRAM/Bandwidth), Storage, and OS topology.
  • ⚡ Real-time Performance Monitoring: Live tracking of system load and identification of resource-hogging processes.
  • 🧊 Thermal & Power Diagnostics: Detects thermal throttling and frequency clipping to resolve unexpected slowness.
  • 🤖 AI/LLM Optimization: Specialized tools for predicting LLM performance, calculating quantization fit, and optimizing runtimes (Ollama, CUDA, Metal).
  • 🛡️ Privacy-First: Automatic anonymization of unique hardware identifiers before any remote transmission.

Installation

For Gemini CLI Users

gemini extension install @yamaru-eu/hardware-probe

For Manual MCP Setup

Add this to your MCP settings file (e.g., npx-config.json or claudedesktopconfig.json):

{
  "mcpServers": {
    "yamaru-probe": {
      "command": "npx",
      "args": ["-y", "@yamaru-eu/hardware-probe"]
    }
  }
}

Available Tools

  • analyzelocalsystem: Full hardware inventory.
  • analyze_performance: Real-time performance metrics and top processes.
  • analyzerampressure: Detailed memory pressure and RSS analysis for deep RAM troubleshooting.
  • checkstoragehealth: Disk SMART health, firmware, and I/O bottleneck analysis.
  • thermal_profile: Real-time CPU/GPU thermal states, fan speeds, and frequency throttling detection.
  • diagnoseantivirusimpact: Detects EDR/Antivirus conflicts and exclusion coverage on dev paths.
  • monitorsystemhealth: Statistical health report (CPU load, RAM usage, temperature) with min/max/avg over a configurable time window (up to 10 minutes).
  • checkllmcompatibility (BETA): Predicts performance for a specific LLM model via remote API.
  • getllmrecommendations (BETA): Recommends the best local models via remote API.
  • analyzeinferenceconfig: Deep-dive into AI runtimes and environment variables.

Skills Integration

When used with Gemini CLI, this extension provides the following expert skills:

  • hardware-performance-expert: Global protocol for system health and troubleshooting.
  • local-inference-optimizer: Specialized logic for fine-tuning local LLM runs.

Development

npm install        # Install dependencies
npm run build      # Compile TypeScript → dist/
npm run test       # Run test suite
npm run inspector  # Test tools in the MCP Inspector

License

Apache 2.0 - Part of the Yamaru Project.

Nothing above is checked by us. What we check is on the safety report.

Hardware Probe: common questions

Is Hardware Probe MCP server safe?
Yes, by our scan: it is graded A (86/100). Read the Hardware Probe safety report
How do I install Hardware Probe?
It runs on your machine. Copy the Claude Code, Cursor, VS Code or Claude Desktop config from the install section.
Does Hardware Probe need an API key?
No secret keys are declared. It reads 1 setting from the environment.
Is Hardware Probe maintained?
The last commit was 111 days ago (2026-07-16). The latest release is v1.1.2.
What can I use instead of Hardware Probe?
Servers from other publishers that do the same job: Image MCP server.
How does Hardware Probe compare with other AI and agents MCP servers?
safety score 86/100 (higher than 75% of 4,460 AI and agents servers); tools 11 (the typical AI and agents server has 6); tools that change things 0% (typical: 0%. Fewer write tools means less an agent can break). Full comparison.

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